Can a state of the art atmospheric general circulation model reproduce recent NAO related variability at the air-sea interface? (original) (raw)
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Predictability of the North Atlantic Oscillation on Intraseasonal Time Scales
Recent evidence suggests more clearly that the intra-seasonal variability of the atmospheric circulation in the North Atlantic, and in particular the North Atlantic Oscillation (NAO), is impacted by tropical convection related to the phase of the Madden-Julian Oscillation (Cassou 2008; Lin et al. 2009). The long-term goals of this project include: (1) Understanding more clearly the mechanisms that mediate the tropical-NAO connection in nature. (2) Assessing the prospects for utilizing this source of tropical predictability to improve dynamical forecasts of the North Atlantic intra-seasonal variations within a seamless prediction system. OBJECTIVES (1) Assess the "perfect model" (idealized) predictability of the NAO at forecast ranges from 1-45 days in the Community Earth System Model (CESM) of NCAR and possibly the Coupled Forecast System Model (CFSv2) of NOAA. (2) To make predictions of observed NAO events at ranges of 1-45 days using CESM and CFSv2. (3) To assess the changes in the predictability and prediction skill when realistic MJO-related tropical diabatic heating is added to the models. (4) To diagnose the dynamical mechanisms by which the tropical heating variations affect the North Atlantic.
Seasonal predictability of the winter NAO from north Atlantic sea surface temperatures
Geophysical Research Letters, 2002
1] We examine the seasonal predictability of the winter (December -January -February) North Atlantic Oscillation (NAO) from lagged north Atlantic sea surface temperatures (SSTs) for the period 1950/1 -2000/1. We identify two lagged modes of SST variability whose principal components (PCs) are correlated significantly to upcoming winter NAO indices. We use linear regression with the PCs as predictors to assess the predictability of the winter NAO from cross-validation over the full period and from replicated real-time forecasts over the recent 15 year period 1986/7 -2000/1. The model anticipates, in early November, the upcoming winter NAO -for a range of NAO indices -with a correlation between 0.47 and 0.63 for 1950/ 1 -2000/1, and between 0.51 and 0.65 for the replicated real-time forecast period. The model also anticipates the correct NAO sign in 67% to 75% of the last 51 winters and in 80% to 93% of the last 15 winters. INDEX TERMS: 4215 Oceanography: General: Climate and interannual variability (3309); 3339 Meteorology and Atmospheric Dynamics: Ocean/ atmosphere interactions (0312, 4504); 1620 Global Change: Climate dynamics (3309). Citation: Saunders, M. A., and B. Qian, Seasonal predictability of the winter NAO from north Atlantic sea surface temperatures, Geophys.
Geophysical Research Letters, 2014
The North Atlantic Oscillation (NAO) is a rapidly decorrelating process that strongly affects the climate over the Atlantic and the surrounding continents. Although the NAO itself is basically unpredictable on seasonal timescales using statistical methods, NAO forcing is here shown to significantly affect sea surface temperatures (SSTs) evolving on those timescales. Results using linear inverse modeling (LIM) imply that the NAO index and its convolution with deterministic SST dynamics account for nearly half the unpredictable component of north tropical Atlantic SST at lead times greater than 9 months; adding this component to hindcasts at a lead of 48 weeks increases correlation with north tropical Atlantic SST from about 0.4 to about 0.6. Rapid fluctuations during boreal winter and spring, when the NAO is strongest, affect SST predictability throughout the entire year.
Evaluation of the North Atlantic Oscillation as simulated by a coupled climate model
1999
The realism of the Hadley Centre's coupled climate model (HadCM2) is evaluated in terms of its simulation of the winter North Atlantic Oscillation (NAO), a major natural mode of the Northern Hemisphere atmosphere that is currently the subject of considerable scienti"c interest. During 1400 y of a control integration with present-day radiative forcing levels, HadCM2 exhibits a realistic NAO associated with spatial patterns of sea level pressure, synoptic activity, temperature and precipitation anomalies that are very similar to those observed. Spatially, the main model de"ciency is that the simulated NAO has a teleconnection with the North Paci"c that is stronger than observed. In a temporal sense the simulation is compatible with the observations if the recent observed trend (from low values in the 1960s to high values in the early 1990s) in the winter NAO index (the pressure di!erence between Gibraltar and Iceland) is ignored. This recent trend is, however, outside the range of variability simulated by the control integration of HadCM2, implying that either the model is de"cient or that external forcing is responsible for the variation. It is shown, by analysing two ensembles, each of four HadCM2 integrations that were forced with historic and possible future changes in greenhouse gas and sulphate aerosol concentrations, that a small part of the recent observed variation may be a result of anthropogenic forcing. If so, then the HadCM2 experiments indicate that the anthropogenic e!ect should reverse early next century, weakening the winter pressure gradient between Gibraltar and Iceland. Even combining this anthropogenic forcing and internal variability cannot explain all of the recent observed variations, indicating either some model de"ciency or that some other external forcing is partly responsible.
Geophysical Research Letters, 2000
The North Atlantic Oscillation (NAO) exhibits variations at interannual to multidecadal time scales and is associated with climate variations over eastern North America, the North Atlantic, Europe, and North Africa. Therefore, it is very important to understand causes of these NAO variations and assess their predictability. It has been hypothesized, based on observations, that sea surface temperature (SST) and sea-ice variations in the North Atlantic Ocean influence the NAO. We describe results of an ensemble of sixteen experiments with an atmospheric general circulation model in which we used observed SST and sea-ice boundary conditions globally during 1949-1993. We show that multiyear NAO and associated climate variations can be simulated reasonably accurately if results from a large number of experiments are averaged. We also show that the ambiguous results of previous NAO modeling studies were strongly influenced by the ensemble size, which was much smaller than that in the present study. The implications of these results for understanding and predictability of the NAO are discussed.
A Study of the Interaction of the North Atlantic Oscillation with Ocean Circulation
Journal of Climate, 2001
Observed patterns of wind stress curl and air-sea heat flux associated with the North Atlantic oscillation (NAO) are used to discuss the response of ocean gyres and thermohaline circulation to NAO forcing and their possible feedback on the NAO. The observations motivate, and are interpreted in the framework of, a simple mathematical model that couples Ekman layers, ocean gyres, and thermohaline circulation to the atmospheric jet stream. Meridional shifts in the zero wind stress curl line are invoked to drive anomalies in ocean gyres, and north-south dipoles in air-sea flux drive anomalous thermohaline circulation. Both gyres and thermohaline circulation play a role in modulating sea surface temperature anomalies and hence, through air-sea interaction, the overlying jet stream. The model, which can be expressed in the form of a delayed oscillator with ocean gyres and/or thermohaline circulation providing the delay, identifies key nondimensional parameters that control whether the ocean responds passively to NAO forcing or actively couples. It suggests that both thermohaline circulation and ocean gyres can play a role in coupled interactions on decadal timescales. 1 The NAO anomaly fields discussed here were computed by regressing NCEP-NCAR reanalysis fields onto the wintermean (DJF) NAO index of . They correspond to a (Hurrell) NAO index of ϩ1 (See Visbeck et al. 1998).
Monthly Weather Review, 2013
December 2010 was unusual both in the strength of the negative North Atlantic Oscillation (NAO) intense atmospheric blocking and the associated record-breaking low temperatures over much of northern Europe. The negative North Atlantic Oscillation for November-January was predicted in October by 8 out of 11 World Meteorological Organization Global Producing Centres (WMO GPCs) of long-range forecasts. This paper examines whether the unusual strength of the NAO and temperature anomaly signals in early winter 2010 are attributable to slowly varying boundary conditions [El Niño-Southern Oscillation state, North Atlantic sea surface temperature (SST) tripole, Arctic sea ice extent, autumn Eurasian snow cover], and whether these were modeled in the Met Office Global Seasonal Forecasting System version 4 (GloSea4). Results from the real-time forecasts showed that a very robust signal was evident in both the surface pressure fields and temperature fields by the beginning of November. The historical reforecast set (hindcasts), used to calibrate and bias correct the real-time forecast, showed that the seasonal forecast model reproduces at least some of the observed physical mechanisms that drive the NAO. A series of ensembles of atmosphere-only experiments was constructed, using forecast SSTs and ice concentrations from November 2010. Each potential mechanism in turn was systematically isolated and removed, leading to the conclusion that the main mechanism responsible for the successful forecast of December 2010 was anomalous ocean heat content and associated SST anomalies in the North Atlantic.
Climate Dynamics, 2005
The North Atlantic Oscillation (NAO) is a major winter climate mode, describing one-third of the inter-annual variability of the upper-level flow in the Atlantic European mid-latitudes. It provides a statistically well-defined pattern to study the predictability of the European winter climate. In this paper, the predictability of the NAO and the associated surface temperature variations are considered using a dynamical prediction approach. Two state-of-the-art coupled atmosphere-ocean ensemble forecast systems are used, namely the seasonal forecast system 2 from the European Centre for Medium Range Weather Forecast (ECMWF) and the multi-model system developed within the joint European project DEMETER (Development of a European Multi-Model Ensemble Prediction System for Seasonal to Inter-annual Prediction). The predictability is defined in probabilistic space using the debiased ranked probability skill score with adapted discretization (RPSS D). The potential predictability of the NAO and its impact are also investigated in a perfect model approach, where each ensemble member is used once as ''observation''. This approach assumes that the climate system is fully represented by the model physics. Using the perfect model approach for the period 1959-2001, it is shown that the mean winter NAO index is potentially predictable with a lead time of 1 month (i.e. from 1st of November). The prediction benefit is rather small (6% skill relative to a reference climatology) but statistically significant. A similar conclusion holds for the near surface temperature variability related to the NAO. Again, the potential benefit is small (5%) but statistically significant. Using the forecast approach, the NAO skill is not statistically significant for the period 1959-2001, while for the period 1987-2001 the skill is surprisingly large (15% relative to a climate prediction). Furthermore, a weak relation is found between the strength of the NAO amplitude and the skill of the NAO. This contrasts with El Nin˜o/Southern Oscillation (ENSO) variability, where the forecast skill is strongly amplitude dependent. In general, robust results are only achieved if the sensitivity with respect to the sample size (both the ensemble size and length of the period) is correctly taken into account.